Senior Machine Learning Scientist (ASR)
Paris, France
- Pay
€70,000–87,200/yearAnnual period assumed — pay source
Location: Paris - Hybrid (3 days in office) Salary: €70,000 - €87,200 We are unable to provide relocation assistance or sponsor a work visa or residence permit for this position. In the Sonos Voice Control team we design the future of AI based interactions to power music control and content discovery for Sonos customers on any control surfaces (Sonos hardware, Sonos Application, Sonos Voice Control).
Read the full posting- Work setup
Hybrid stated — work setup source
Senior Machine Learning Scientist (ASR) Location: Paris - Hybrid (3 days in office) Salary: €70,000 - €87,200 We are unable to provide relocation assistance or sponsor a work visa or residence permit for this position.
Read the full posting- Employment
- Unconfirmed
What you’ll work on
Full postingWork in the Audio Machine Learning team of Sonos Voice Control, together with a group of experienced machine learning engineers and researchers
Design and train state-of-the-art machine learning models for automatic speech recognition and wakeword detection
Ensure our models perform the best they can on specialised domains, such as music entities, loudspeaker control and home automation
From the employer’s posting
What You’ll Do Work in the Audio Machine Learning team of Sonos Voice Control, together with a group of experienced machine learning engineers and researchers Design and train state-of-the-art machine learning models for automatic speech recognition and wakeword detection
Work in the Audio Machine Learning team of Sonos Voice Control, together with a group of experienced machine learning engineers and researchers Design and train state-of-the-art machine learning models for automatic speech recognition and wakeword detection Ensure our models perform the best they can on specialised domains, such as music entities, loudspeaker control and home automation
Design and train state-of-the-art machine learning models for automatic speech recognition and wakeword detection Ensure our models perform the best they can on specialised domains, such as music entities, loudspeaker control and home automation Define and implement the data strategy for training and testing, as well as audio augmentation to reflect the far-field acoustic conditions of our products
What you’ll bring
All qualificationsCore experience
- 8+ years experience in machine learning research & engineering for voice applications
- Experience in owning the whole model development lifecycle from data generation, training, evaluation to shipping models for production
Preferred experience
- Experience in developing models for real-time, low latency, streaming ASR
- Experience in model adaptation techniques for large entity catalogs (shallow-fusion biasing, rescoring, error correction)
- Understanding of the particular challenges of far-field ASR, including acoustics and data augmentation for model training and evaluation
Qualification wording
8+ years experience in machine learning research & engineering for voice applications
Experience in owning the whole model development lifecycle from data generation, training, evaluation to shipping models for production
Experience in developing models for real-time, low latency, streaming ASR
Experience in model adaptation techniques for large entity catalogs (shallow-fusion biasing, rescoring, error correction)
Understanding of the particular challenges of far-field ASR, including acoustics and data augmentation for model training and evaluation
Education & alternatives
- 8+ years experience in machine learning research & engineering for voice applications - A PhD or Master’s degree in computer science, or a related technical field (or equivalent experience) - In-depth knowledge of speech processing (ASR, wakeword detection, audio features), particularly latest architectures for automatic speech recognition (RNN-T, Transformers)
Tools in this posting
- C
- Python
- Rust
- C++
- PyTorch
Source — Tool mentions in context
- Advanced knowledge of Python and common machine learning toolkits (PyTorch) - Intermediate knowledge of a low-level compiled language (Rust, C, C++) Preferred Skills
- Experience in owning the whole model development lifecycle from data generation, training, evaluation to shipping models for production - Advanced knowledge of Python and common machine learning toolkits (PyTorch) - Intermediate knowledge of a low-level compiled language (Rust, C, C++)
Job description
At Sonos we want to create the ultimate listening experience for our customers and know that it starts by listening to each other. As part of the Sonos team, you’ll collaborate with people of all styles, skill sets, and backgrounds to realize our vision while fostering a community where everyone feels included and empowered to do the best work of their lives.
Senior Machine Learning Scientist (ASR)Location: Paris - Hybrid (3 days in office)
Salary: €70,000 - €87,200
We are unable to provide relocation assistance or sponsor a work visa or residence permit for this position.
In the Sonos Voice Control team we design the future of AI based interactions to power music control and content discovery for Sonos customers on any control surfaces (Sonos hardware, Sonos Application, Sonos Voice Control).
We are seeking an experienced ML engineer to join the Audio Machine Learning team, focused on building the next generation of Sonos Voice Control. The team develops all audio-based components of Sonos' in-house voice assistant solution, including far-field automatic speech recognition (ASR), wakeword detection, and speech enhancement. The team is also in charge of shipping those models to production and running them efficiently and fast on multiple types of hardware.
What You’ll Do
Work in the Audio Machine Learning team of Sonos Voice Control, together with a group of experienced machine learning engineers and researchers
Design and train state-of-the-art machine learning models for automatic speech recognition and wakeword detection
Ensure our models perform the best they can on specialised domains, such as music entities, loudspeaker control and home automation
Define and implement the data strategy for training and testing, as well as audio augmentation to reflect the far-field acoustic conditions of our products
Maintain and improve scalable and efficient training and evaluation pipelines
Contribute to the team’s roadmap and set the technical direction for the ASR domain
Mentor other team members on ML best practices, experiment planning, and model analysis
Collaborate with the cloud backend and embedded engineering teams to ensure our models perform the best they can in the different environments
What You’ll Need
Basic Qualifications
8+ years experience in machine learning research & engineering for voice applications
A PhD or Master’s degree in computer science, or a related technical field (or equivalent experience)
In-depth knowledge of speech processing (ASR, wakeword detection, audio features), particularly latest architectures for automatic speech recognition (RNN-T, Transformers)
Experience in owning the whole model development lifecycle from data generation, training, evaluation to shipping models for production
Advanced knowledge of Python and common machine learning toolkits (PyTorch)
Intermediate knowledge of a low-level compiled language (Rust, C, C++)
Preferred Skills
Experience in developing models for real-time, low latency, streaming ASR
Experience in model adaptation techniques for large entity catalogs (shallow-fusion biasing, rescoring, error correction)
Understanding of the particular challenges of far-field ASR, including acoustics and data augmentation for model training and evaluation
MLOps and software engineering for efficient training and data infrastructure
Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. If you don’t have 100% of the skills listed, we strongly encourage you to apply if interested.
#LI-hybrid
Your profile will be reviewed and you'll hear from us once we have an update. At Sonos we take the time to hire right and appreciate your patience.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on sonos.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Location: Paris - Hybrid (3 days in office) Salary: €70,000 - €87,200 We are unable to provide relocation assistance or sponsor a work visa or residence permit for this position. In the Sonos Voice Control team we design the future of AI based interactions to power music control and content discovery for Sonos customers on any control surfaces (Sonos hardware, Sonos Application, Sonos Voice Control).
- Location & working pattern
Paris, France
Senior Machine Learning Scientist (ASR) Location: Paris - Hybrid (3 days in office) Salary: €70,000 - €87,200 We are unable to provide relocation assistance or sponsor a work visa or residence permit for this position.
More source context
Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. If you don’t have 100% of the skills listed, we strongly encourage you to apply if interested. #LI-hybrid Your profile will be reviewed and you'll hear from us once we have an update. At Sonos we take the time to hire right and appreciate your patience.
- Work authorization
Location: Paris - Hybrid (3 days in office) Salary: €70,000 - €87,200 We are unable to provide relocation assistance or sponsor a work visa or residence permit for this position. In the Sonos Voice Control team we design the future of AI based interactions to power music control and content discovery for Sonos customers on any control surfaces (Sonos hardware, Sonos Application, Sonos Voice Control).
- Status in our records
- Active
- First seen by us
- May 5, 2026
- Recorded sightings
- 87
- Last seen by us
- Oct 7, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.